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IJCAI
2007
13 years 9 months ago
Using Linear Programming for Bayesian Exploration in Markov Decision Processes
A key problem in reinforcement learning is finding a good balance between the need to explore the environment and the need to gain rewards by exploiting existing knowledge. Much ...
Pablo Samuel Castro, Doina Precup
JSS
2008
157views more  JSS 2008»
13 years 7 months ago
Can k-NN imputation improve the performance of C4.5 with small software project data sets? A comparative evaluation
Missing data is a widespread problem that can affect the ability to use data to construct effective prediction systems. We investigate a common machine learning technique that can...
Qinbao Song, Martin J. Shepperd, Xiangru Chen, Jun...
AIEDU
2004
71views more  AIEDU 2004»
13 years 7 months ago
Using Intelligent Feedback to Improve Sourcing and Integration in Students' Essays
Learning and reasoning from multiple documents requires students to employ the skills of sourcing (i.e., attending to and citing sources) and information integration (i.e., making ...
Mary Anne Britt, Peter M. Wiemer-Hastings, Aaron A...
CVPR
2004
IEEE
14 years 9 months ago
Object-Based Image Retrieval Using the Statistical Structure of Images
We propose a new Bayesian approach to object-based image retrieval with relevance feedback. Although estimating the object posterior probability density from few examples seems in...
Derek Hoiem, Rahul Sukthankar, Henry Schneiderman,...
CVPR
2004
IEEE
14 years 9 months ago
A Graphical Model Framework for Coupling MRFs and Deformable Models
This paper proposes a new framework for image segmentation based on the integration of MRFs and deformable models using graphical models. We first construct a graphical model to r...
Rui Huang, Vladimir Pavlovic, Dimitris N. Metaxas